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https://files.pythonhosted.org/packages/d4/e2/df3543e8ffdab68f5acc73f613de9c2b155ac47f162e725dcac87c521c11/tokenizers-0.10.3-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (3.3MB)\n","\u001b[K     |████████████████████████████████| 3.3MB 42.8MB/s \n","\u001b[?25hRequirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torch>=1.6.0->sentence-transformers) (3.7.4.3)\n","Requirement already satisfied: pillow>=5.3.0 in /usr/local/lib/python3.7/dist-packages (from torchvision->sentence-transformers) (7.1.2)\n","Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.7/dist-packages (from scikit-learn->sentence-transformers) (1.0.1)\n","Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from nltk->sentence-transformers) (1.15.0)\n","Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->datasets) 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already satisfied: click in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers<5.0.0,>=4.6.0->sentence-transformers) (7.1.2)\n","Building wheels for collected packages: sentence-transformers\n","  Building wheel for sentence-transformers (setup.py) ... \u001b[?25l\u001b[?25hdone\n","  Created wheel for sentence-transformers: filename=sentence_transformers-2.0.0-cp37-none-any.whl size=126711 sha256=a533d92fe07ef629089e0f3d0fcfcd91fbf65420c00b7c46a351fcc4c3259a46\n","  Stored in directory: /root/.cache/pip/wheels/38/d2/98/d191289a877a34c68aa67e05179521e060f96394a3e9336be6\n","Successfully built sentence-transformers\n","\u001b[31mERROR: transformers 4.8.2 has requirement huggingface-hub==0.0.12, but you'll have huggingface-hub 0.0.13 which is incompatible.\u001b[0m\n","Installing collected packages: huggingface-hub, sacremoses, tokenizers, transformers, sentencepiece, sentence-transformers, xxhash, fsspec, datasets\n","Successfully installed datasets-1.8.0 fsspec-2021.6.1 huggingface-hub-0.0.13 sacremoses-0.0.45 sentence-transformers-2.0.0 sentencepiece-0.1.96 tokenizers-0.10.3 transformers-4.8.2 xxhash-2.0.2\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":220,"referenced_widgets":["b3803181d0c8469c86fdc3d7c5fd248d","b424b0b120574187a899dcf6e6630c0d","790c80f265c74e89abb7346327b06913","5a44b51373a74bf291cbbdf42a97824e","6d2fc03f88384e4fa5dc49192696485f","de1e19bffe414e6facda81c36af2facd","c4f43e9837664cb19b781210ab1b81df","ac796f522e8340f7acc968321247a58a","59883ef110d1468f8965197745e5f1f5","10c2476ccebe4a1cbe17109fbe1f3ce5","19cfa619be984d1da06d621d9fe63675","ec5cb81c0bf743e197db54b344ef4a8a","aa47871249ae4e57ac570e3c4786b898","b4ed1ad07ce64e58b28b101b6c5a5a35","41e01299eabc41e8ba751144d40c3106","024d83144b5c40cf83ca2351c89a98af","86997849b31b44feb94173ee98f040c8","5197c821abe64ff98b1bdd0a7739a6cd","e2e2eb813c8048aaae492b3ff25f8fc9","88d9aa267eeb4a08b4365a11c3c4b901","b73cb08605c346b5828b7eaff06f6780","2443100345bc4e4783a39d6b2c93f474","5efb55132c5747dbba1a7d8ac06ccd3e","b845117ac4de480987c8d4e28873c296","1655b0bb6704455aa0fbf0e7891d69da","adb9137d03db4f809730323bbebe914b","9f17a5bae5f246d197b05ec107ed63fe","25f8d10b64c7455cb4d56045d9afe681","39d93d5f435f4ee9a8674d28abea6dc2","ef80dd4dc15d45e8aa824dc5a1a1dbf6","098ca0fcf0aa499c8780059b5f0c744e","f6fb399446ea432caef675ae1d339e15","d7935fa82bc6491fb1d0caac1dfe9b65","377035ce4afa458286de0286830ca8a6","4a31d57bef6849fc8b6a14a97c8a9ea1","41caa06467af4529a2cdb73502855a80","bc85633d268648349c836c57c8af5087","726d171deca94a2c82e8eda2b06f9cdd","baeea6a8c5f0402c9f20b41db4b39244","00ecebdd5950456abc77ffbcc5165495","91b9f4b54608425289ebbde9e0e3e54e","34228a5e734c46ed81d7a34e275cc358","ca53771c60b248b591b58340b8360520","efb830c816a34b17aeecaa2790475380","76df95b327a44345b55291570d55b68b","60c811d256e048f69fc93026f18226f0","64dac7a15ee143c18348437f428e26ef","cd4b2bb938da41e7883cf302d9ee73d8"]},"id":"gTFdMJqFMsnp","executionInfo":{"status":"ok","timestamp":1625418418869,"user_tz":-180,"elapsed":37858,"user":{"displayName":"meysam asgari chenaghlu","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GgN-uRJ5KciT9X_sZpZ4pOpEANlj5GCtXuY2ecq=s64","userId":"13491140841572947804"}},"outputId":"2c019503-210e-42c7-c0cf-0c371902a6b7"},"source":["from datasets import load_dataset \n","imdb = load_dataset(\"imdb\")"],"execution_count":2,"outputs":[{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"b3803181d0c8469c86fdc3d7c5fd248d","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=1916.0, style=ProgressStyle(description…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"59883ef110d1468f8965197745e5f1f5","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=1054.0, style=ProgressStyle(description…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n","Downloading and preparing dataset imdb/plain_text (download: 80.23 MiB, generated: 127.02 MiB, post-processed: Unknown size, total: 207.25 MiB) to /root/.cache/huggingface/datasets/imdb/plain_text/1.0.0/e3c66f1788a67a89c7058d97ff62b6c30531e05b549de56d3ab91891f0561f9a...\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"86997849b31b44feb94173ee98f040c8","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=84125825.0, style=ProgressStyle(descrip…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"1655b0bb6704455aa0fbf0e7891d69da","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\r"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"d7935fa82bc6491fb1d0caac1dfe9b65","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\r"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"91b9f4b54608425289ebbde9e0e3e54e","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\rDataset imdb downloaded and prepared to /root/.cache/huggingface/datasets/imdb/plain_text/1.0.0/e3c66f1788a67a89c7058d97ff62b6c30531e05b549de56d3ab91891f0561f9a. Subsequent calls will reuse this data.\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"wUFlPw0irgOe","executionInfo":{"status":"ok","timestamp":1625418418874,"user_tz":-180,"elapsed":23,"user":{"displayName":"meysam asgari chenaghlu","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GgN-uRJ5KciT9X_sZpZ4pOpEANlj5GCtXuY2ecq=s64","userId":"13491140841572947804"}}},"source":["imdb = imdb.shuffle()"],"execution_count":3,"outputs":[]},{"cell_type":"code","metadata":{"id":"60A2Iz7gRXdd","executionInfo":{"status":"ok","timestamp":1625418419282,"user_tz":-180,"elapsed":424,"user":{"displayName":"meysam asgari chenaghlu","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GgN-uRJ5KciT9X_sZpZ4pOpEANlj5GCtXuY2ecq=s64","userId":"13491140841572947804"}}},"source":["imdb_x = [x for x in imdb['train'][:1000]['text']] \n","labels = [x for x in imdb['train'][:1000]['label']] \n","import pandas as pd \n","pd.DataFrame(imdb_x, \n","             columns=[\"text\"]).to_excel( \n","                                 \"imdb.xlsx\", \n","                                  index=None) "],"execution_count":4,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":424},"id":"IHUxuNHpRcg3","executionInfo":{"status":"ok","timestamp":1625418423843,"user_tz":-180,"elapsed":849,"user":{"displayName":"meysam asgari chenaghlu","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GgN-uRJ5KciT9X_sZpZ4pOpEANlj5GCtXuY2ecq=s64","userId":"13491140841572947804"}},"outputId":"2724df05-a3ec-41a6-c450-f3797c8eac15"},"source":["pd.read_excel(\"KHMER.xlsx\") "],"execution_count":5,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>ខណៈពេលដែលជំនាន់ដើម ១៩៣២ ជាមួយប្រេសស្តុនហ្វតគឺល...</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>ភាពយន្តអាមេរិចដែលនិយាយច្រើនបំផុតនៅក្នុងមហោស្រព...</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>ប៊ីងហ្គោគឺជាហ្គេមល្បែងអុកគឺជាឈ្មោះ។ កម្រមានអេក...</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>មានហេតុផលជាច្រើនដែលធ្វើឱ្យខ្ញុំវាយតម្លៃសោណុសយ៉...</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>ខ្ញុំគិតថាការមើលវីដេអូការងារស្តីពីការអនុលោមតាម...</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>995</th>\n","      <td>ខ្ញុំបានឃើញខ្សែភាពយន្តនេះជាលើកដំបូងនៅទូរទស្សន៍...</td>\n","    </tr>\n","    <tr>\n","      <th>996</th>\n","      <td>ខ្សែភាពយន្តនេះល្អណាស់។ ខ្ញុំមិនមែនជាអ្នកគាំទ្រ...</td>\n","    </tr>\n","    <tr>\n","      <th>997</th>\n","      <td>ផលប៉ះពាល់ភ្លាមៗគឺជាខ្សែភាពយន្តទី ៤ នៃខ្សែភាពយន...</td>\n","    </tr>\n","    <tr>\n","      <th>998</th>\n","      <td>កាលពី ៣ ឆ្នាំមុនរ៉ាជែល (ថេរ៉េសហ្វ្រែលវែល) កំពុ...</td>\n","    </tr>\n","    <tr>\n","      <th>999</th>\n","      <td>ខ្ញុំមិនមានចំណាប់អារម្មណ៍ខ្លាំងពេកក្នុងការមើលរ...</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>1000 rows × 1 columns</p>\n","</div>"],"text/plain":["                                                  text\n","0    ខណៈពេលដែលជំនាន់ដើម ១៩៣២ ជាមួយប្រេសស្តុនហ្វតគឺល...\n","1    ភាពយន្តអាមេរិចដែលនិយាយច្រើនបំផុតនៅក្នុងមហោស្រព...\n","2    ប៊ីងហ្គោគឺជាហ្គេមល្បែងអុកគឺជាឈ្មោះ។ កម្រមានអេក...\n","3    មានហេតុផលជាច្រើនដែលធ្វើឱ្យខ្ញុំវាយតម្លៃសោណុសយ៉...\n","4    ខ្ញុំគិតថាការមើលវីដេអូការងារស្តីពីការអនុលោមតាម...\n","..                                                 ...\n","995  ខ្ញុំបានឃើញខ្សែភាពយន្តនេះជាលើកដំបូងនៅទូរទស្សន៍...\n","996  ខ្សែភាពយន្តនេះល្អណាស់។ ខ្ញុំមិនមែនជាអ្នកគាំទ្រ...\n","997  ផលប៉ះពាល់ភ្លាមៗគឺជាខ្សែភាពយន្តទី ៤ នៃខ្សែភាពយន...\n","998  កាលពី ៣ ឆ្នាំមុនរ៉ាជែល (ថេរ៉េសហ្វ្រែលវែល) កំពុ...\n","999  ខ្ញុំមិនមានចំណាប់អារម្មណ៍ខ្លាំងពេកក្នុងការមើលរ...\n","\n","[1000 rows x 1 columns]"]},"metadata":{"tags":[]},"execution_count":5}]},{"cell_type":"code","metadata":{"id":"fxE6DY6NRgUn","executionInfo":{"status":"ok","timestamp":1625418427329,"user_tz":-180,"elapsed":799,"user":{"displayName":"meysam asgari chenaghlu","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GgN-uRJ5KciT9X_sZpZ4pOpEANlj5GCtXuY2ecq=s64","userId":"13491140841572947804"}}},"source":["imdb_khmer = list(pd.read_excel(\"KHMER.xlsx\").text) "],"execution_count":6,"outputs":[]},{"cell_type":"code","metadata":{"id":"7nioiNGqcXDn","executionInfo":{"status":"ok","timestamp":1625418428978,"user_tz":-180,"elapsed":610,"user":{"displayName":"meysam asgari chenaghlu","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GgN-uRJ5KciT9X_sZpZ4pOpEANlj5GCtXuY2ecq=s64","userId":"13491140841572947804"}}},"source":["from sklearn.model_selection import train_test_split"],"execution_count":7,"outputs":[]},{"cell_type":"code","metadata":{"id":"UB1qHD3rRjhv","executionInfo":{"status":"ok","timestamp":1625418428981,"user_tz":-180,"elapsed":13,"user":{"displayName":"meysam asgari chenaghlu","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GgN-uRJ5KciT9X_sZpZ4pOpEANlj5GCtXuY2ecq=s64","userId":"13491140841572947804"}}},"source":["train_x, test_x, train_y, test_y, khmer_train, khmer_test = train_test_split(imdb_x, labels, imdb_khmer, test_size = 0.2, random_state = 1) "],"execution_count":8,"outputs":[]},{"cell_type":"code","metadata":{"id":"s0ELOlYCRmAh","colab":{"base_uri":"https://localhost:8080/","height":609,"referenced_widgets":["5566df79eb0c4e28a647081e63fa3463","29c9907f72664998a10f6c82ab48c4fc","770e912991874b2b82d5ecc710f43b5a","33b13866c73b4885969b2a4f70179575","71e05ae5b53e40bf9da3262cd592d6bf","d984b35e306840ccbb4ce941f08fcb96","5cbcc18e16c14add8c170fa209babf50","a957d432d5874e1e9ddc90f652d02956","a306e5a641974d9f8d79d41046edeef0","8f0ff2e9843a42c69560d89c54b28f6f","ad0c60b441624df39f1124865388bd8d","318c063a1a8e4356a3fc2caedfafcc44","345f64b03393485da5e235cf0bd2c735","43ea447d97244527a2c1fa5446074e26","c80374a3895f4c18bc1730438e17434b","72193d6aec3844bc9a249050937dee31","043b108aeecb49a9a2a57af2136577d3","24a4de97147048f79a0b74f1cb91d208","7775f1fec99d4fa298e12f0963f290a7","37b58768f8694d588f8c619e5ef639ec","f2b95f21bd914b558c04c922780df0a7","91099f9a948e457390a250bf4349756d","61f35cb6412440209c0db09db9b85b53","84f794295e624014be79c592e9d10aa9","b8e6c8f0e3a54b4bab5279aa255f4fd5","2e1ef92d1ba34c21b86e88e6447e9542","517376891a4049dfaa1b48bd3bf512d7","6def7de5dd934c74b180fc0f5ecaec9c","a145deb5fd784754ae95d1117f8b56d7","f91a2bebb1ce448f946b5c42e070a964","035a1fe6cfd44bb2a9d778871ee03b38","a12854771e0d48928982e1932db58593","117536bac3e44d258785c5399226df5e","8d906fa887eb45968c6d65482a5b4028","caf87d92b4474c01807b3ebf1fc8f637","0f1aff9290364b17a676abad67184939","e737e1dd5ad643888087bdfa99640f31","d4ed2a73e864400cada47855d94106d7","d55734e522ab46908763712b54def3b7","a1414ae859a6483e9f6bc2b6543f73a8","e475c7364c7f4d7493d3463b682b476f","add2617721dc460ebe84be20a279d57c","e80c48f75ce24fe6b71df469bab5cd59","4743d2135cef41e1bb78660912fdc2d5","002b5d7c98ca4273a7ec8970b451c0f2","e94214a09cf54dd3a40bd77cb815c2ed","8ee3bc02254f4129b2a25ab7f5a95fb1","d7a6000ad58546cc8818a7dcac9c6813","2a64e60f02e74b03b09cc716152c62cc","8b06f74e8b3d4055b171daa466442ab8","53a764e83741443bbc624b6fe5555db4","2eb2c619c4dd44de9f754f219ffccc30","11854f9df23941c696d95aa46f7f0357","f91ae331c37642d8985be2169f2cd580","f0e1ca3e19d149c0b0b1d100fa3c0178","c60665ecf3534be4a7cb440922bd7154","6008b546539043478801f48598bc6ab1","cbae2ee94bde446794a574ea0282d3f2","105d95ed3178414fae3196a35290c84a","7bf01eff0a7b413db09de5fd430a2ad9","4d60dece46084cd68a934b75f9a2ca3d","31e18ca06e444ae8afd34e7416fed799","5807e4ff036f40c6a9128d6db326d245","c00341059e734425806aa705c2f0c679","d251be52a61d4274b9eb0de1f8ac8c51","5da979e7bd214bc58b47c2140548829a","3fed7d1a1249409cb7e04099c26a0dc4","bc18c9cfda60481dbf69bcb9cd3322c4","d37b5d009f1f40dfb02c335fda102fd7","c892e469eb2e478f884d99996fbebc7e","0c94e93f81634af9a964af2ae2ab6a42","bd083a6525934b7d925114adb0f6abd2","bb628c1a02a64667b506003901ae0086","87f9acef75934ffab3a69f558843b5ec","ea59e8327ea344449f5d6f00d082fb14","71a23c01915f40ce8fe8b1b963079825","8d2045b805ee4c3e93be0ae7cfd9fcc6","0274e1ef57e647d2934aad4c9bb7aeea","39b8979cf9f54ad7b6d1c4bb9ec42b04","e2dd4cadeb9b4e6cb067ee298c9bd85c","5b12b7e706c74898b08a897f6a97c71a","416dcf77fe2e44148e418ca50de060be","27d96cced45140059a1658097b1986b1","ebb27aef868048a495b6a40754313f64","00b440a6e06e4dbf80e18bb50eca5e16","27bb5b8aba86431785e077464e707219","8f1089b3f54149a685120a66c09db12e","1e43b9f7ee2c45a886ada6c8333d109e","51fdd0c41e314630875ea85c92061908","dfc346bbed434a7283030f0651118533","be206549f12b46b28f243e983162f1c7","50cc9ffd8b6445549cb4cf7df982ee3d","dd09d0c4ed7d4fe48dd946e71c6e2e52","24a038bd243a4586b93687753a742405","62a80e3a556b4dfc8d1a8ef5b1d8e78a","e045973f36054722bb74074ed3da54a2"]},"executionInfo":{"status":"ok","timestamp":1625418479286,"user_tz":-180,"elapsed":48973,"user":{"displayName":"meysam asgari chenaghlu","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GgN-uRJ5KciT9X_sZpZ4pOpEANlj5GCtXuY2ecq=s64","userId":"13491140841572947804"}},"outputId":"9c790e7d-ecf7-4564-9217-9d4c6f2e084f"},"source":["from sentence_transformers import SentenceTransformer \n","model = SentenceTransformer(\"stsb-xlm-r-multilingual\") "],"execution_count":9,"outputs":[{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"5566df79eb0c4e28a647081e63fa3463","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=574.0, style=ProgressStyle(description_…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"a306e5a641974d9f8d79d41046edeef0","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=3679.0, style=ProgressStyle(description…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"043b108aeecb49a9a2a57af2136577d3","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=709.0, style=ProgressStyle(description_…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"b8e6c8f0e3a54b4bab5279aa255f4fd5","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=122.0, style=ProgressStyle(description_…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"117536bac3e44d258785c5399226df5e","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=229.0, style=ProgressStyle(description_…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"e475c7364c7f4d7493d3463b682b476f","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=1112253233.0, style=ProgressStyle(descr…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"2a64e60f02e74b03b09cc716152c62cc","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=53.0, style=ProgressStyle(description_w…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"6008b546539043478801f48598bc6ab1","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=5069051.0, style=ProgressStyle(descript…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"d251be52a61d4274b9eb0de1f8ac8c51","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=150.0, style=ProgressStyle(description_…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"bb628c1a02a64667b506003901ae0086","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=9096735.0, style=ProgressStyle(descript…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"5b12b7e706c74898b08a897f6a97c71a","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=505.0, style=ProgressStyle(description_…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"51fdd0c41e314630875ea85c92061908","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=190.0, style=ProgressStyle(description_…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"tPJMKF6jRoR1","executionInfo":{"status":"ok","timestamp":1625418500095,"user_tz":-180,"elapsed":20810,"user":{"displayName":"meysam asgari chenaghlu","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GgN-uRJ5KciT9X_sZpZ4pOpEANlj5GCtXuY2ecq=s64","userId":"13491140841572947804"}}},"source":["encoded_train = model.encode(train_x) \n","encoded_test = model.encode(test_x) \n","encoded_khmer_test = model.encode(khmer_test) "],"execution_count":10,"outputs":[]},{"cell_type":"code","metadata":{"id":"BuyQGkuTRrLE","executionInfo":{"status":"ok","timestamp":1625418500108,"user_tz":-180,"elapsed":26,"user":{"displayName":"meysam asgari chenaghlu","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GgN-uRJ5KciT9X_sZpZ4pOpEANlj5GCtXuY2ecq=s64","userId":"13491140841572947804"}}},"source":["import numpy as np \n","train_y = np.array(train_y) \n","test_y = np.array(test_y) "],"execution_count":11,"outputs":[]},{"cell_type":"code","metadata":{"id":"EDj8VB7zRuJk","executionInfo":{"status":"ok","timestamp":1625418504905,"user_tz":-180,"elapsed":4816,"user":{"displayName":"meysam asgari chenaghlu","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GgN-uRJ5KciT9X_sZpZ4pOpEANlj5GCtXuY2ecq=s64","userId":"13491140841572947804"}}},"source":["import tensorflow as tf \n","input_ = tf.keras.layers.Input((768,)) \n","classification = tf.keras.layers.Dense( \n","                                1, \n","                                activation=\"sigmoid\")(input_) \n","classification_model = tf.keras.Model(input_, classification) \n","classification_model.compile( \n","               loss=tf.keras.losses.BinaryCrossentropy(), \n","               optimizer=\"Adam\", \n","               metrics=[\"accuracy\", \"Precision\", \"Recall\"]) "],"execution_count":12,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"speAOhBdRyOD","executionInfo":{"status":"ok","timestamp":1625418510867,"user_tz":-180,"elapsed":5971,"user":{"displayName":"meysam asgari chenaghlu","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GgN-uRJ5KciT9X_sZpZ4pOpEANlj5GCtXuY2ecq=s64","userId":"13491140841572947804"}},"outputId":"c27e9048-2ebe-480b-f9ab-d697e96a0a83"},"source":["classification_model.fit( \n","                     x = encoded_train, \n","                     y = train_y, \n","                     validation_data=(encoded_test, test_y), \n","                     epochs = 20) "],"execution_count":13,"outputs":[{"output_type":"stream","text":["Epoch 1/20\n","25/25 [==============================] - 4s 15ms/step - loss: 0.6512 - accuracy: 0.6025 - precision: 0.6229 - recall: 0.6110 - val_loss: 0.5918 - val_accuracy: 0.7100 - val_precision: 0.7257 - val_recall: 0.7523\n","Epoch 2/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.5478 - accuracy: 0.7362 - precision: 0.7321 - recall: 0.7828 - val_loss: 0.5429 - val_accuracy: 0.7100 - val_precision: 0.7684 - val_recall: 0.6697\n","Epoch 3/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.5097 - accuracy: 0.7638 - precision: 0.7738 - recall: 0.7757 - val_loss: 0.5219 - val_accuracy: 0.7150 - val_precision: 0.7653 - val_recall: 0.6881\n","Epoch 4/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.4894 - accuracy: 0.7912 - precision: 0.7986 - recall: 0.8043 - val_loss: 0.5150 - val_accuracy: 0.7150 - val_precision: 0.7653 - val_recall: 0.6881\n","Epoch 5/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.4749 - accuracy: 0.7912 - precision: 0.8000 - recall: 0.8019 - val_loss: 0.5065 - val_accuracy: 0.7350 - val_precision: 0.7745 - val_recall: 0.7248\n","Epoch 6/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.4613 - accuracy: 0.7925 - precision: 0.8048 - recall: 0.7971 - val_loss: 0.5006 - val_accuracy: 0.7550 - val_precision: 0.7727 - val_recall: 0.7798\n","Epoch 7/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.4543 - accuracy: 0.8062 - precision: 0.8028 - recall: 0.8353 - val_loss: 0.5122 - val_accuracy: 0.7150 - val_precision: 0.7708 - val_recall: 0.6789\n","Epoch 8/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.4468 - accuracy: 0.8000 - precision: 0.8076 - recall: 0.8115 - val_loss: 0.4996 - val_accuracy: 0.7450 - val_precision: 0.7685 - val_recall: 0.7615\n","Epoch 9/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.4429 - accuracy: 0.8037 - precision: 0.8032 - recall: 0.8282 - val_loss: 0.5032 - val_accuracy: 0.7350 - val_precision: 0.7692 - val_recall: 0.7339\n","Epoch 10/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.4335 - accuracy: 0.8100 - precision: 0.8141 - recall: 0.8258 - val_loss: 0.5043 - val_accuracy: 0.7250 - val_precision: 0.7596 - val_recall: 0.7248\n","Epoch 11/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.4300 - accuracy: 0.8087 - precision: 0.8107 - recall: 0.8282 - val_loss: 0.5091 - val_accuracy: 0.7250 - val_precision: 0.7647 - val_recall: 0.7156\n","Epoch 12/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.4270 - accuracy: 0.8200 - precision: 0.8313 - recall: 0.8234 - val_loss: 0.5166 - val_accuracy: 0.7250 - val_precision: 0.7755 - val_recall: 0.6972\n","Epoch 13/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.4216 - accuracy: 0.8175 - precision: 0.8212 - recall: 0.8329 - val_loss: 0.5107 - val_accuracy: 0.7200 - val_precision: 0.7624 - val_recall: 0.7064\n","Epoch 14/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.4166 - accuracy: 0.8150 - precision: 0.8173 - recall: 0.8329 - val_loss: 0.5174 - val_accuracy: 0.7150 - val_precision: 0.7600 - val_recall: 0.6972\n","Epoch 15/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.4124 - accuracy: 0.8150 - precision: 0.8219 - recall: 0.8258 - val_loss: 0.5085 - val_accuracy: 0.7300 - val_precision: 0.7570 - val_recall: 0.7431\n","Epoch 16/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.4093 - accuracy: 0.8225 - precision: 0.8274 - recall: 0.8353 - val_loss: 0.5120 - val_accuracy: 0.7100 - val_precision: 0.7476 - val_recall: 0.7064\n","Epoch 17/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.4053 - accuracy: 0.8175 - precision: 0.8182 - recall: 0.8377 - val_loss: 0.5116 - val_accuracy: 0.7150 - val_precision: 0.7500 - val_recall: 0.7156\n","Epoch 18/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.4057 - accuracy: 0.8150 - precision: 0.8265 - recall: 0.8186 - val_loss: 0.5129 - val_accuracy: 0.7350 - val_precision: 0.7593 - val_recall: 0.7523\n","Epoch 19/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.3981 - accuracy: 0.8313 - precision: 0.8365 - recall: 0.8425 - val_loss: 0.5174 - val_accuracy: 0.7250 - val_precision: 0.7596 - val_recall: 0.7248\n","Epoch 20/20\n","25/25 [==============================] - 0s 4ms/step - loss: 0.3962 - accuracy: 0.8375 - precision: 0.8416 - recall: 0.8496 - val_loss: 0.5226 - val_accuracy: 0.7150 - val_precision: 0.7600 - val_recall: 0.6972\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["<tensorflow.python.keras.callbacks.History at 0x7f8d141fdc10>"]},"metadata":{"tags":[]},"execution_count":13}]},{"cell_type":"code","metadata":{"id":"QlBd4JMNR1H-","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1625418510869,"user_tz":-180,"elapsed":19,"user":{"displayName":"meysam asgari chenaghlu","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GgN-uRJ5KciT9X_sZpZ4pOpEANlj5GCtXuY2ecq=s64","userId":"13491140841572947804"}},"outputId":"5a10e0b0-0d87-4214-efd1-75151d99a293"},"source":["classification_model.evaluate(x = encoded_khmer_test,\n","                              y = test_y) "],"execution_count":14,"outputs":[{"output_type":"stream","text":["7/7 [==============================] - 0s 3ms/step - loss: 0.5945 - accuracy: 0.7250 - precision: 0.7015 - recall: 0.8624\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["[0.5944913625717163,\n"," 0.7250000238418579,\n"," 0.7014925479888916,\n"," 0.8623853325843811]"]},"metadata":{"tags":[]},"execution_count":14}]},{"cell_type":"code","metadata":{"id":"JTlUVGb5sdwK"},"source":[""],"execution_count":null,"outputs":[]}]}